# mst: Multiscalar Typology (3 deviations) In MTA: Multiscalar Territorial Analysis

 mst R Documentation

## Multiscalar Typology (3 deviations)

### Description

Compute a multiscalar typology according to the three relative deviations (general: G, territorial: T and spatial: S). The elementary units are classified in eight classes according to their three relative positions.

### Usage

``````mst(x, gdevrel, tdevrel, sdevrel, threshold, superior = FALSE)
``````

### Arguments

 `x` a sf object or a dataframe including gdev, tdev and sdev columns. `gdevrel` name of the general relative deviation variable in x. `tdevrel` name of the territorial relative deviation variable in x. `sdevrel` name of the spatial relative deviation variable in x. `threshold` defined to build the typology (100 is considered as the average). `superior` if TRUE, deviation values must be greater than threshold. If FALSE, deviation values must be lower than threshold.

### Value

a vector in x including the mst typology. Values are classified in 8 classes following their respective position above/under the threshold:

Typology (which deviation is above/under the threshold):

• 0: none

• 1: G

• 2: T

• 3: G and T

• 4: S

• 5: G and S

• 6: T and S

• 7: G, T and S

### Examples

``````# Load data
library(sf)
com <- st_read(system.file("metroparis.gpkg", package = "MTA"), layer = "com", quiet = TRUE)

# Prerequisite  - Compute the 3 deviations
com\$gdev <- gdev(x = com, var1 = "INC", var2 = "TH")
com\$tdev <- tdev(x = com, var1 = "INC", var2 = "TH", key = "EPT")
com\$sdev <- sdev(x = com, var1 = "INC", var2 = "TH", order = 1)

# Multiscalar typology - wealthiest territorial units
# Compute mst
com\$mstW <- mst(x = com, gdevrel = "gdev", tdevrel = "tdev", sdevrel = "sdev",
threshold = 125, superior = TRUE)

#Multiscalar typology - lagging territorial units
# Compute mst
com\$mstP <- mst(x = com, gdevrel = "gdev", tdevrel = "tdev", sdevrel = "sdev",
threshold = 75, superior = FALSE)
``````

MTA documentation built on Nov. 2, 2023, 5:06 p.m.